Misconceptions disrupting the revival of Indian languages

New Delhi: India is a nation of varieties. With 22 officially recognized languages and a countless number of dialects, India flaunts a plethora of varied diversities.

A near 200 years of British rule undeniably corroded the rich heritage with language coming under severe attack of the colonial powers. However, the irony is that Indian languages continue to face the same treatment.

However, the irony is that Indian languages continue to face the same treatment even after the Britishers left.

What makes matters worse is the fact that the number of students opting for English medium schools is escalating by leaps and bounds. Notably, in the last five years, the number of students studying in English medium have doubled.

Surprisingly, it was in the Hindi bastion of Uttar Pradesh and Bihar that witnessed this exceptional growth.

Despite the government’s plan to implement measures to promote vernacular languages, English became the primary choice of the guardians.

The very idea that education in English would facilitate a job encouraged the parents to opt for the foreign language instead of the language that linked them to their very roots.

Unfortunately, the misconception that the chance of getting a job are much higher if a student comes from the English background has adversely affected our mother tongues.

Promotional campaigns by the government will not encourage people to study in their own language, but assurance of work and livelihood can lure people to read in their native language.

A paradigm change needs to be incorporated.

The inferiority complex associated with studying in local languages needs to be shunned. Rather, one must take pride in studying in the language which he uses for crying, laughing, calling his mother and expressing love.

The wrong notion that studying in English makes one smart pose a tough challenge before Indian languages. Carrying an English novel and flaunting it in public has become an endemic.

Strategic measures need to be implemented to revive our languages. It has to be fiercely promoted that even carrying a novel written in an Indian local language and reading it in a public place also make you look equally smart.

Microsoft to pay $250,000 to help them catch chip bugs. Wikimedia Commons

Microsoft creates a new kind of AI

This can translate Chinese to English just like humans

The translator makes little mistakes

A team of Microsoft researchers, including one of Indian-origin, has created an Artificial Intelligence (AI)-powered machine system that can translate sentences of news articles from Chinese to English with the same quality and accuracy as humans.

Researchers from the company’s Asia and US labs said their system achieved human parity on a commonly-used test set of news stories — called “newstest2017” — that was released at a conference recently, a blog post said late on Wednesday.

This Ai can expertly translate Chinese into English. Pixabay

According to Arul Menezes, an IIT-Bombay alumni and Partner Research Manager of Microsoft’s machine translation team, the team set out to prove that its systems could perform about as well as a person when it used a language pair — like Chinese to English — for which there is a lot of data.

“Given the best-case situation as far as data and availability of resources goes, we wanted to find out if we could actually match the performance of a professional human translator,” said Menezes.

To ensure the results were both accurate and at par with what people would have done, the team hired external bilingual human evaluators who compared Microsoft’s results to two independently produced human reference translations.

“Hitting human parity in a machine translation task is a dream that all of us have had. We just did not realise we would be able to hit it so soon,” said Xuedong Huang, Technical Fellow in charge of Microsoft’s speech, natural language and machine translation efforts.

To reach the human parity milestone on this dataset, three research teams in Microsoft’s Beijing and Redmond, Washington, research labs worked together to make the system more accurate.

“Much of our research is really inspired by how we humans do things,” said Tie-Yan Liu, Principal Research Manager with Microsoft Research Asia in Beijing.

The team used dual-learning method. Every time they sent a sentence through the system to be translated from Chinese to English, the research team also translated it back from English to Chinese.

The accuracy rate is high too. Wikimedia

That’s similar to what people might do to make sure that their automated translations were accurate, and it allowed the system to refine and learn from its own mistakes. Dual learning, which was developed by the Microsoft research team, can also be used to improve results in other AI tasks.

Another method, called deliberation networks, is similar to how people edit and revise their own writing by going through it again and again. The researchers taught the system to repeat the process of translating the same sentence over and over, gradually refining and improving the response, Microsoft said. IANS